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Raman and Infrared (IR) spectroscopies provide information about the structure, functional groups and environment of the molecules in the sample. In combination with a microscope, these techniques can also be used to study molecular distributions in heterogeneous samples. Over the past few decades Raman and IR microspectroscopy based techniques have been extensively used to understand fundamental biology and responses of living systems under diverse physiological and pathological conditions. The spectra from biological systems are complex and diverse, owing to their heterogeneous nature consisting of bio-molecules such as proteins, lipids, nucleic acids, carbohydrates etc. Sometimes minor differences may contain critical information. Therefore, interpretation of the results obtained from Raman and IR spectroscopy is difficult and to overcome these intricacies and for deeper insight we need to employ various data mining methods. These methods must be suitable for handling large multidimensional data sets and for exploring the complete spectral information simultaneously. The effective implementation of these multivariate data analysis methods requires the pretreatment of data. The preprocessing of raw data helps in the elimination of noise (unwanted signals) and the enhancement of discriminating features. This review provides an outline of the state-of-the-art data processing tools for multivariate analysis and the various preprocessing methods that are widely used in Raman and IR spectroscopy including imaging for better qualitative and quantitative analysis of biological samples.

Infectious diseases caused by bacteria still pose major diagnostic challenges in spite of the availability of various molecular approaches. Irrespective of the type of infection, rapid identification of the causative pathogen with a high degree of sensitivity and specificity is essential for initiating appropriate treatment. While existing methods like PCR possess high sensitivity, they are incapable of identifying the viability status of the pathogen and those which can, like culturing, are inherently slow. To overcome these limitations, we developed a diagnostic platform based on Raman microspectroscopy, capable of detecting biochemical signatures from a single bacterium for identification as well as viability assessment. The study also establishes a decontamination protocol for handling live pathogenic bacteria which does not affect identification and viability testing, showing applicability in the analysis of sputum samples containing pathogenic mycobacterial strains. The minimal sample processing along with multivariate analysis of spectroscopic signatures provides an interface for automatic classification, allowing the prediction of unknown samples by mapping signatures onto available datasets. Also, the novelty of the current work is the demonstration of simultaneous identification and viability assessment at a single bacterial level for pathogenic bacteria.

Raman spectroscopy and resonance Raman spectroscopy are widely used to study bacteria and their responses to different environmental conditions. In the present study, the identification of a novel resonance Raman peak for Escherichia coli, recorded with 633 nm laser excitation is discussed. A peak at 740 cm−1 is observed exclusively with 633 nm excitation but not with 514 nm or 785 nm excitation. This peak is absent in the lag phase but appears in the log phase of bacterial growth. The intensity of the peak increases at high temperature (45 °C) compared with growth at low temperature (25 °C) or the physiological temperature (37 °C). Although osmotic stress lowered bacterial growth, the intensity of this peak was unaffected. However, treatment with chemical uncouplers of oxidative phosphorylation resulted in significantly lower intensity of this Raman band, indicating its possible involvement in respiration. Cytochromes, a component of bacterial respiration‚ can show resonance enhancement at 633 nm due to the presence of a shoulder in that region depending on the type and conformation of cytochrome. Therefore, the peak intensity was monitored in different genetic mutants of E. coli lacking cytochromes. This peak is absent in the Escherichia coli mutant lacking cydB, but not ccmE, demonstrating the contribution of cytochrome bd subunit II in the peak’s origin. In future, this newly found cytochrome marker can be used for biochemical assessment of bacteria exposed to various conditions. Overall, this finding opens the scope for use of red laser excitation in resonance Raman in monitoring stress and respiration in bacteria.

Cascading energy landscapes through funneling has been postulated as a mechanistic route for achieving the lowest energy configuration of a macromolecular system (such as proteins and polymers). In particular, understanding the molecular mechanism for the melting and crystallization of polymers is a challenging fundamental question. The structural modifications that lead to the melting of poly(ethylene glycol) (PEG) are investigated here. Specific Raman bands corresponding to different configurations of the PEG chain have been identified, and the molecular structural dynamics of PEG melting have been addressed using a combination of Raman spectroscopy, 2D Raman correlation and density functional theory (DFT) calculations. The melting dynamics of PEG have been unambiguously explained along the C–O bond rotation coordinate. Cascading energy landscapes through funneling has been postulated as a mechanistic route for achieving lowest energy configuration of a macromolecular system (such as, proteins and polymers). In particular, understanding molecular mechanism of melting and crystallization of polymers is a challenging fundamental question. The structural modifications that lead to melting of PEG are investigated here. Specific Raman bands corresponding to different configurations of the PEG chain have been identified and the molecular structural dynamics of PEG melting has been addressed using Raman spectroscopy, two-dimensional Raman correlation and DFT calculations.

ObjectiveThis study aims to detect pathogenic Escherichia coli (E. coli) bacteria using non-destructive fluorescence microscopy and micro-Raman spectroscopy.ResultsRaman vibrational spectroscopy provides additional information regarding biochemical changes at the cellular level. We have used two nanomaterials zinc oxide nanoparticles (ZnO-NPs) and gold nanoparticles (Au-NPs) to detect pathogenic E. coli. The scanning electron microscope (SEM) with energy dispersive X-ray (EDAX) spectroscopy exhibit surface morphology and the elemental composition of the synthesized NPs. The metal NPs are useful contrast agents due to the surface plasmon resonance (SPR) to detect the signal intensity and hence the bacterial cells. The changes due to the interaction between cells and NPs are further correlated to the change in the surface charge and stiffness of the cell surface with the help of the fluorescence microscopic assay.ConclusionsWe conclude that when two E. coli strains (MTCC723 and MTCC443) and NPs are respectively mixed and kept overnight, the growth of bacteria are inhibited by ZnO-NPs due to changes in cell membrane permeability and intracellular metabolic system under fluorescence microscopy. However, SPR possessed Au-NPs result in enhanced fluorescence of both pathogens. In addition, with the help of Raman microscopy and element analysis, significant changes are observed when Au-NPs are added with the two strains as compared to ZnO-NPs due to protein, lipid and DNA/RNA induced conformational changes.

We demonstrate observation of Raman signals of different analytes adsorbed on carbonaceous materials, such as, chemically reduced graphene, graphene oxide (GO), multi-walled carbon nanotube (MWCNT), graphite and activated carbon. The analytes selected for the study were Rhodamine 6G (R6G) (in resonant conditions), Rhodamine B (RB), Nile blue (NBA), Crystal Violet (CV) and acetaminophen (paracetamol). All the analytes except paracetamol absorb and fluoresce in the visible region. In this article we provide experimental evidence of the fact that observation of Raman signals of analytes on such carbonaceous materials are more due to resonance effect, suppression of fluorescence and efficient adsorption and that this property in not unique to graphene or nanotubes but prevalent for various type of carbon materials.

A common technique used to differentiate bacterial species and to determine evolutionary relationships is sequencing their 16S ribosomal RNA genes. However, this method fails when organisms exhibit high similarity in these sequences. Two such strains that have identical 16S rRNA sequences are Mycobacterium indicus pranii (MIP) and Mycobacterium intracellulare. MIP is of significance as it is used as an adjuvant for protection against tuberculosis and leprosy; in addition, it shows potent anti-cancer activity. On the other hand, M. intracellulare is an opportunistic pathogen and causes severe respiratory infections in AIDS patients. It is important to differentiate these two bacterial species as they co-exist in immuno-compromised individuals. To unambiguously distinguish these two closely related bacterial strains, we employed Raman and resonance Raman spectroscopy in conjunction with multivariate statistical tools. Phenotypic profiling for these bacterial species was performed in a kinetic manner. Differences were observed in the mycolic acid profile and carotenoid pigments to show that MIP is biochemically distinct from M. intracellulare. Resonance Raman studies confirmed that carotenoids were produced by both MIP as well as M. intracellulare, though the latter produced higher amounts. Overall, this study demonstrates the potential of Raman spectroscopy in differentiating two closely related mycobacterial strains.

Breast cancer is the most prevalent cause of cancer-associated death in women the world over, but if detected early it can be treated successfully. Therefore, it is important to diagnose this disease at an early stage and to understand the biochemical changes associated with cellular transformation and cancer progression. Deregulated lipid metabolism has been shown to contribute to cell transformation as well as cancer progression. In this study, we monitored the biomolecular changes associated with the transformation of a normal cell into an invasive cell associated with breast cancer using Raman microspectroscopy. We have utilized primary normal breast cells, and immortalized, transformed, non-invasive, and invasive breast cancer cells. The Raman spectra were acquired from all these cell lines under physiological conditions. The higher wavenumber (2800–3000 cm−1) and lower wavenumber (700–1800 cm−1) range of the Raman spectrum were analyzed and we observed increased lipid levels for invasive cells. The Raman spectral data were analyzed by principal component–linear discriminant analysis (PC-LDA), which resulted in the formation of distinct clusters for different cell types with a high degree of sensitivity. The subsequent testing of the PC-LDA analysis via the leave-one-out cross validation approach (LOOCV) yielded relatively high identification sensitivity. Additionally, the Raman spectroscopic results were confirmed through fluorescence staining tests with BODIPY and Nile Red biochemical assays. Furthermore, Raman maps from the above mentioned cells under fixed conditions were also acquired to visualize the distribution of biomolecules throughout the cell. The present study shows the suitability of Raman spectroscopy as a non-invasive, label-free, microspectroscopic technique, having the potential of probing changes in the biomolecular composition of living cells as well as fixed cells.

Fiber laser field is typically dominated by rare earth ions as gain material in the core of a silica optical waveguide. Due to their specific emission wavelengths, rare‐earth‐doped fiber lasers are available only at few predefined wavelengths. However, quantum dots (QDs) are materials which show tunable emission with change in size and composition. Due to such tunability, QDs seem to be promising candidates for obtaining fiber lasers at a spectrum of wavelengths which is not possible using rare earth ions. To replace rare earth ions with QDs, it is of paramount importance that QDs show signatures of optical gain. Herein, the synthesis of asymmetric pod‐shaped CdSe/CdS QDs is reported, which demonstrate efficient gain on pumping. The intrinsic gain properties of the QDs are evaluated through transient absorption (TA) spectroscopy. Later, the exquisite QDs are used to fabricate specialty fibers from which amplified spontaneous emission (ASE) is obtained using continuous wave laser pump at room temperature. Finally, emission signal stability is checked by studying photobleaching and controlling the concentration of the QDs. In this report, anisotropic CdSe/CdS core/shell quantum dots (QDs) with high optical gain (QDs) have been used as a gain medium in optical fibers for fiber laser applications. They use continuous wave pump power to exhibit amplified spontaneous emission in the tailored QD fibers at ambient temperature.

The analysis of body fluids is desirable to minimize the invasiveness of diagnostic tests and non-destructive forensic investigations. In this study, surface-enhanced Raman spectroscopy (SERS) is employed for sensitive and reproducible detection of biomolecule focusing on ‘hot spots’ generation and automated flow system. Here, we have demonstrated how the plasmon frequency of nanoparticles can be tuned using different aggregating agents for optimal SERS signals. We have compared the effect of different aggregating agents on silver colloids and the resulting enhancement in Raman signals for Tryptophan which is an important amino acid present as an integral component of various body fluids including blood, saliva, tears, and cerebrospinal fluid. The automated segmented flow system, Lab-on-a-chip (LOC), is employed to trap the analyte in droplets while obtaining reproducible SERS spectra of Tryptophan at μM concentration. Further for a thorough interpretation of enhanced vibrational modes of Tryptophan, a theoretical approach has been applied. By combining both experimental and computational approaches we have identified the most preferable site of Tryptophan for interaction with metal nanoparticles and accurately assigned the enhanced Raman bands. The present study demonstrates that the union of SERS and microfluidics has the potential for spectral fingerprinting of biomolecules present in body fluids with high sensitivity.